Papers by Michal Gregor

2 papers
Investigating Language and Retrieval Bias in Multilingual Previously Fact-Checked Claim Detection (2026.eacl-long)

Copied to clipboard

Challenge: Recent advances in multilingual Large Language Models have enabled powerful capabilities for cross-lingual fact-checking.
Approach: They evaluate six open-source multilingual LLMs across 20 languages using a fully multilingual prompting strategy.
Outcome: The proposed model performs better on high-resource languages than on low-resourced ones.
Large Language Models for Multilingual Previously Fact-Checked Claim Detection (2025.findings-emnlp)

Copied to clipboard

Challenge: a new study evaluates large language models for multilingual previously fact-checked claim detection . authors assess seven LLMs across 20 languages in monolingual and cross-lingual settings .
Approach: They evaluate large language models for multilingual previously fact-checked claim detection . they find they perform well for high-resource languages, struggle with low-resourced languages .
Outcome: The proposed model performs well for high-resource languages, but struggle with low-resourced languages.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations